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The course builds upon a Bachelor-level introductory course in econometrics. A central goal is to deepen the knowledge on the linear regression model in various directions, including regression with instrumental variables and heteroskedastic errors. In addition, maximum likelihood estimation and the related asymptotic tests are introduced.

The course starts with a review of the linear regression model and the small-sample and asymptotic properties of the ordinary least squares estimator and statistical inference concerning its parameters. A large part of the course is devoted to the detection of and addressing violations of the basic assumptions of the linear regression model. In particular, statistical inference based on the ordinary least squares estimator under heteroskedastic or autocorrelated errors are considered. The instrumental variables and the generalised method of moments estimators, useful in the case of endogenous regressors as well as the method of maximum likelihood, widely applicable in econometrics, also introduced. Throughout the course, the emphasis is on the practical aspects of econometric modelling instead of the foundations of statistical inference. The models and methods are illustrated by means of Monte Carlo simulations and empirical applications.

  • Completion method: contact teaching
  • Schedule: can be found in Course Page and Sisu
  • Study materials: can be found in Moodle
    • Tips for enrolling in a Moodle course area can be found here

Please register for the course in the UH Sisu with your UH username, further instructions can be found here.

    • Code: no equivalent code
    • Target groups: MSc (not suitable for PhD students)
    • Credit points: 5
    • Credit transfer: apply for inclusion in Sisu
    • Code: 2689
      • can be also used to substitute the mandadatory course 26031Applied Empirical methods in economics, 5 cr
    • Target groups: MSc (not suitable for PhD students)
    • Credit points:
      • 2689: 6 cr
      • 26031: 5 cr
    • Credit transfer: apply for substitution in Sisu
    • Code: ECOM-G314

    • Target groups: MSc (not suitable for rMSc and PhD students)

    • Credit points: 5

    • Not suitable for PhD students

After the course, the student should:

  • Be very familiar with the interpretation of and statistical inference in the linear regression model in the cross-sectional context 
  • Be familiar with the properties of the ordinary least squares, instrumental variables and the generalised method of moments estimators 
  • Understand the basic properties of the maximum likelihood estimator and the related asymptotic tests 
  • Be able to critically read empirical economic research employing methods covered in the course, to identify their potential methodological problems, to compare alternative econometric model specifications and to assess the adequacy of empirical results 
  • Be able to apply the models and methods covered in the course in empirical research